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SDR 13-425 – HSR Study

 
SDR 13-425
Understanding Women's Disparities in Satisfaction with VA Health Care (DISC Women)
Susan L. Zickmund, PhD
VA Pittsburgh Healthcare System University Drive Division, Pittsburgh, PA
Pittsburgh, PA
Funding Period: August 2013 - March 2016
BACKGROUND/RATIONALE:
Patient satisfaction, a VHA mission-critical performance measure, is a widely accepted measure of provider and healthcare system performance that is linked to the the overall VA mission. While VHA is committed to equal treatment for all Veterans, data show disparities in Veteran satisfaction with care.

This proposal augments IIR 10-144 Racial and Ethnic Disparities in Satisfaction with VA Care study (DISC), which focuses on racial and ethnic disparities in satisfaction with VA care, by adding interviews with a cohort of racially and ethnically diverse female Veterans to examine gender disparities in care overall and within racial and ethnic subgroups.

OBJECTIVE(S):
The Speecific Aims of this study are the following:

Specific Aim 1. To examine the associations between gender and satisfaction with overall, outpatient, inpatient, and 13 domains of VA health care based on a quantitative survey.

Specific Aim 2. To identify themes of satisfaction and dissatisfaction with overall, outpatient, inpatient, and 13 domains of VA health care in a sample of female and male Veterans based on a qualitative interview.

Specific Aim 3: To use mixed methods to examine gender differences in themes of satisfaction and dissatisfaction with overall, outpatient, inpatient, and 13 domains of VA health care.

METHODS:
Using a random sample drawn from 25 VA Medical Centers, we conducted telephone interviews from the VA Pittsburgh Healthcare System using both closed and open-ended questions with 600 African American, Hispanic, and white women Veterans as well as a small sample of other minority Veterans.

This mixed-methods design allows for the examination of the direct, mediated and/or moderated associations of gender/race/ethnicity on satisfaction outcomes. The open-ended questions will provide data for a formal qualitative analysis of both reasons for satisfaction and dissatisfaction with VA health care and ways to improve VA care that are gender and culturally sensitive. Finally, random effects modeling of coded qualitative data will be used to formally estimate and test gender/racial/ethnic differences.

Because the random effects modeling uses open-ended, qualitative data this statistical analysis allows our study to go beyond reliance on pre-established satisfaction items, and instead capture very specific reasons for satisfaction and dissatisfaction with VA health care as described by the women Veterans themselves

FINDINGS/RESULTS:
Between June 2013 and November 2014, 7,565 Veterans were mailed invitations, 2,412 consented to screening, 1,929 were eligible to participate, 1,392 consented, and 1,222 completed interviews.

Specific aim 1: 47% of patients described themselves as very satisfied (VS) with their overall VA care. The 3 domains with the highest VS rating were: cost (78%), clinic physical facility (75%), and pharmacy services (74%). The 3 domains with the lowest VS rating were: interpersonal communication (58%), pain management (54%), and access (46%). Based on the estimated Age-Adjusted results from the multinomial logistic regression, white females were less satisfied with outpatient care (p=0.03), respect (p=0.04) and cost of care (p=0.02) than were white males. Black females were less satisfied with pharmacy (p=0.03) and were more satisfied with specialist care (p=0.02) than black males.

Specific aim 2: For the qualitative analysis, the 4 satisfaction themes with the largest overall gender differences were the experience of good care at the VA (39% f vs. 47% m), satisfaction with scheduling timing (16% f vs. 11% m), good interactions (16% f vs. 11% m), and the ability to call or e-mail provider (9% f vs. 5% m). Similarly the 4 dissatisfaction themes with the largest overall gender differences were the experience of poor care at the VA (30% f vs. 25% m), dissatisfaction with scheduling timing (34% f vs. 27% m), having negative interactions (14% f vs. 11% m) and dissatisfaction with the scheduling process (13% f vs. 8% m).

Specific aim 3: We are currently integrating the quantitative and qualitative databanks.

IMPACT:
Given the VA's commitment to providing high quality care to all patients, it is critical to understand the reasons underlying gender disparities in care. The unique concerns of a diverse female group of Veterans are critical to capture, so that effective and appropriate interventions can be developed to reduce disparities in satisfaction.

This supplemental expansion of our DISC study uses an innovative approach to pinpoint key modifiable areas of dissatisfaction for African American and Hispanic female Veterans, as well as patient-identified potential solutions to improve care for women in general. This is the first step toward the development of targeted interventions designed to improve satisfaction with VA health care among the growing proportion of diverse female Veterans.


External Links for this Project

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PUBLICATIONS:

Journal Articles

  1. Jones AL, Fine MJ, Taber PA, Hausmann LRM, Burkitt KH, Stone RA, Zickmund SL. National Media Coverage of the Veterans Affairs Waitlist Scandal: Effects on Veterans' Distrust of the VA Health Care System. Medical care. 2021 Jun 1; 59(Suppl 3):S322-S326. [view]
  2. Zickmund SL, Burkitt KH, Gao S, Stone RA, Jones AL, Hausmann LRM, Switzer GE, Borrero S, Rodriguez KL, Fine MJ. Racial, Ethnic, and Gender Equity in Veteran Satisfaction with Health Care in the Veterans Affairs Health Care System. Journal of general internal medicine. 2018 Mar 1; 33(3):305-331. [view]
Conference Presentations

  1. Zickmund SL, Borrero S, Burkitt KH, Hausmann L, Switzer GE, Stone RA, Gao S, Rodriguez K, Fine MJ. Gender differences in satisfaction with VA health care. Paper presented at: VA HSR&D / QUERI National Meeting; 2015 Jul 10; Philadelphia, PA. [view]


DRA: Health Systems
DRE: none
Keywords: none
MeSH Terms: none

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